Borrowing it
Nothing to install: this file belongs to AgentEvalHQ/AgentEval. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AgentEvalHQ/AgentEval/main/.github/instructions/maf-doctor.instructions.mdgit clone --depth 1 https://github.com/AgentEvalHQ/AgentEvalWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/agentevalhq/agenteval/maf-doctor)<a href="https://agentmods.dev/instructions/agentevalhq/agenteval/maf-doctor"><img src="https://agentmods.dev/badge/instructions/agentevalhq/agenteval/maf-doctor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/agentevalhq/agenteval/maf-doctor"><img src="https://agentmods.dev/badge/instructions/agentevalhq/agenteval/maf-doctor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00855 | $0.00855 |
| Opus 5.5 | $0.00342 | $0.00342 |
| Sonnet 5.5 | $0.00171 | $0.00171 |
| Haiku 4.5 | $0.00085 | $0.00085 |
Grade C, and why
AgentEval maf-doctor.instructions.md scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- Managed by `maf-doctor init` — this file is fully overwritten on every re-run. For durable, hand-authored guidance, use .github/copilot-instructions.md instead (init never touches it). --> What it actually says
Using maf-doctor for Microsoft Agent Framework code
This repository uses Microsoft Agent Framework. The maf-doctor MCP server (also called "MAF Doctor") is installed and exposes tools for diagnosing, fixing, and migrating MAF code.
Before answering MAF questions or proposing changes:
-
Always call
MafDoctorfirst on the repo path to get the current health grade (A-F) and the top issues. Don't speculate about MAF quality without this baseline. -
For any
[Obsolete]warning,CS0618/CS0246diagnostic, or build failure mentioning a MAF type — callMafRunCs0618Hunt(full project scan) orMafApiSafety(single symbol) BEFORE suggesting a fix. The maf-doctor registry has curated fix recipes that supersede your training data — MAF ships breaking changes every minor version, so training data is likely outdated. -
To fix issues —
MafAutoFixAll --dry-runthen apply handles the mechanical rules deterministically (offer this first; the rewrites are tested). To fix everything, run themaf-remediateprompt (or just ask "fix all the issues maf-doctor found"): it grades → plans → autofixes → then works each semantic finding. Every finding carries aconfidence(certain/high/heuristic); aheuristicfinding may be a false positive — confirm it withMafExplainFindingbefore editing. Get the plan viaMafDoctor(format: "plan")(human) or--plan --json(structured manifest); per-rule fix + false-positive guidance lives in themaf-remediation-playbookskill. -
When designing a new MAF agent or workflow — call
MafNewAgent/MafNewExecutorfor scaffolds, orMafSimulateWorkflowfor topology preview. Don't reconstruct patterns from memory. -
For deep architectural / security / migration questions — run the
maf-review(best-practice audit),maf-audit(pre-migration scan + plan),maf-migrate(execute a migration-plan.md), ormaf-debug(diagnose a symptom) MCP prompts —initwires these up automatically, no extra setup needed. If.github/agents/was also copied in from the maf-doctor source repo (GitHub Copilot only — see the toolkit's init-reference.md), the equivalent@maf-best-practice-reviewer,@maf-auditor,@maf-migration, or@maf-incident-responderpersonas work the same way. -
To migrate FROM Semantic Kernel TO MAF (a cross-framework port, NOT a MAF version bump) — call
MafDetectSourceFramework(CLI:maf-doctor migrate-scan) to inventory SK usage and scope it, then run themaf-migrate-fromprompt (or the@maf-cross-migrationagent, if.github/agents/was also copied in). It scaffolds a new MAF project beside the original and ports it construct-by-construct, non-destructively. The mapping lives atmaf://migrate-from?source=semantic-kernel.
maf-doctor tools are MAF-version-aware via applies_to_codebases markers
in the registry — they know which fix applies to which MAF version. Defer to
the tools.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 62 lines · 855 tokens per session scan C 3d9cfee75e36
AgentEval maf-doctor.instructions.md is an instructions file published in the GitHub repository AgentEvalHQ/AgentEval (157 stars, last pushed 4d ago), licensed MIT. It adds 855 tokens to every session, about $0.0034 per session on Opus 5.5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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